Credibility - Often called internal validity, refers to the believability and trustworthiness of the findings. This depends more on the richness of the data gathered than on the quantity of data. The participants of the study are the only ones that decide if the results actually reflect the phenomena being studied and therefore, it is important that participants feel the findings are credible and accurate. Triangulation is a commonly used method for verifying accuracy that involves cross-checking information from multiple perspectives. The link in Resources Links on the left describes different types of triangulation methods.

Transferability - Often called external validity, refers to the degree that the findings of the research can be transferred to other contexts by the readers. This means that the results are generalizable and can be applied to other similar settings, populations, situations and so forth. Researchers should thoroughly describe the context of the research to assist the reader in being able to generalize the findings and apply them appropriately.

Dependability - Otherwise known as reliability, refers to the consistency with which the results could be repeated and result in similar findings. The dependability of the findings also lends legitimacy to the research method. Because the nature of qualitative research often results in an ever changing research setting and changing contexts, it is important that researcher document all aspects of any changes or unexpected occurrences to further explain the findings. This is also important for other researchers who may want to replicate the study.

Confirmability - A measure of the objectivity used in evaluating the results, describes how well the research findings are supported by the actual data collected when examined by other researchers. Researchers bring their own unique perspectives to the research process and data interpretation can be somewhat subjective in qualitative research. If findings are corroborated or confirmed by others who examine the data, then no inappropriate biases impacted the data analysis.